Bibliographic record
Abstract
新能源汽车自19世纪末诞生至今已经100多年，一直没有成功扩散到主流市场；近十年才实现高速发展。是哪些因素影响着新能源汽车创新扩散？蔚来和理想汽车是在此次新能源汽车浪潮中脱颖而出的两家新造车公司，相继在2018年、2020年上市，这两家公司有着截然不同的发展路线。蔚来在以充电为主流路线的背景下，选择了探索换电技术，需要持续投入巨额资金；理想在以纯电动为主流趋势的背景下，选择了增程式技术，路线前景不明。蔚来和理想汽车代表了中国新能源汽车市场中两种不同的路线，究竟哪一种创新扩散路线能够获得竞争优势？接下来，新能源汽车在创新扩散中还会遇到哪些挑战？蔚来和理想该如何应对？
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".